Open Land Use - the Current Status and Steps Forward
1. Open Land Use current status and steps
forward – data are 3D, Google searchable and
OLU4Africa
Karel Charvát, Bente Lilja Bye, Dmitri Kožuch, Tomas Mildorf, Petr Uhlir
SciDataCon 2018: The Digital Frontiers of Global Science
Gaborone (Botswana) 8th November 2018
2. • Open Land Use Map (https://sdi4apps.eu/open_land_use/ ):
– Initiative that emerged from Plan4Business project,
that aims at creating detailed European Open Land
Use map, that could be used for planning activities by
local authorities, businessmen, citizens
– The product is as detailed possible (somewhere even
at parcels level) harmonized, seamless land use map
of Europe created from various sources of open vector
data, that is published and available for free download
Background
3. Open Land Use Map (OLU)
• Harmonisation and integration of
heterogeneous land use and land cover
data
• Reusing the INSPIRE land use data
specifications → transformation into a
common INSPIRE compliant data model
• Mapping different classifications →
HILUCS
• Uniform visualisation
• Using RDF model – in preparation
08.11.2018
SciDataCon 2018: The
Digital Frontiers of Global 3
4. • Corine Land Cover 2006
• Urban Atlas
• Cadastral data
• Land Parcel Identification System – LPIS
• Spatial plans
• Other sources
Different
level of
detail
Different
geometry
Open Land Use Map
08.11.2018
SciDataCon 2018: The
Digital Frontiers of Global 4
5. Methodology of data integration
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SciDataCon 2018: The
Digital Frontiers of Global 5
7. Existing Open Land Use Maps
SciDataCon 2018: The
Digital Frontiers of Global
Czech Republic Flanders
Latvia
Slovakia
08.11.2018 7
8. Open Land Use
• Seamless coverage of most of the Europe
(around 45 000 000 objects)
• Where it is possible reliable local sources of
data are used which have certain quality,
certain update period, persistent identifier
• Data model is based on Inspire Existing Land
Use object data model
• It however has more detailed metadata on the
object’s metadata – stating exactly where did
the object originate as seen on the image
on the right.
08.11.2018
SciDataCon 2018: The
Digital Frontiers of Global 8
9. Open Land Use page
08.11.2018
SciDataCon 2018: The
Digital Frontiers of Global 9
16. • Open Land Use Map for Africa (https://goo.gl/Rn32HD):
– Attempt to create Open Land Use Map for Africa
based on available vector data (mainly from Open
Street Map and Africover) during the last year
Inspire hackathon in Kehl
– The attempt has shown the insufficiency of vector
data sources for creation of vector seamless
harmonized land use map of Africa
Background
19. Motivation
• Lack of land use data in Africa
• Increased availability of satellite imagery with
spatial resolution suitable even for classifying
individual buildings (for instance Sentinel
products, Landsat products available from
https://scihub.copernicus.eu/,
https://earthexplorer.usgs.gov/ )
• Immense leap in usage of machine learning
methods in many spheres (including image
recognition, image classification)
20. Product
• Seamless harmonized vector land use map of
municipalities in Africa together with relevant
spatial planning legislation and socio-
economic data
• Internet platform for providing services (data
download, data upload, data search, data
visualizations) for users/customers
21. Aims
• Humanitarian :
– Help sustainable development of municipalities, help
optimize resource management, help reduce such
problems as deforestation, unregulated urban growth,
extensive exploitation of natural resources
• Business :
– Create sustainable business platform that would
provide various data services and bring main
stakeholders (authorities, businessmen, citizens)
together
23. Use of satellite data
• Sentinel – 2 Imagery :
– Will be classified and used for creating base land
use map of municipalities
24. Use of satellite data derivatives
Datasets will be used mainly for masking areas:
• Global Urban Footprint (4 arc seconds)
• CCI Land Cover 20 m land cover map of Africa
• Land Cover map over Africa based on PROBA-
V 100 m data
25. Workflow for base landuse map
• Prepare the classification techniques that would be used for each HILUCS class if
applicable (some classes such as financial services, community services etc. are
difficult to deduce from 10 m satellite imagery)
• Limit each HILUCS class to land cover context (classes) in which it can exist
• Create training and evaluation samples for each HILUCS class (automatically with
help of Sentinel 2 data cropped by respective features from available vector
databases (Open Street Map for instance) )
• Create and test models
• Mask out inappropriate land cover classes within municipality and run selected
classification technique for identifying each class in selected municipality
• Process all municipalities one by one
26. Workflow
• Create search/download module for investors
• Create view/crowdsource module for citizens
• Create edit/upload/download module for
authorities
• Contact authorities to collect spatial plans/spatial
planning legislation/socio-economic data,
promote product among citizens
27. Thanks for your attention!
https://micka.lesprojekt.cz
https://goo.gl/Rn32HDcharvat@plan4all.eu
www.plan4all.eu
https://www.researchgate.net/profile/Karel_Charvat2
https://twitter.com/charvat_kar
https://www.facebook.com/karel.charvat.3
https://www.linkedin.com/in/karelcharvat/